Word2vec (Japanese Wikipedia)

Analysis of information sources in references of the Wikipedia article "Word2vec" in Japanese language version.

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1code.google.com

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aclweb.org

Levy, Omer; Goldberg, Yoav; Dagan, Ido (2015). “Improving Distributional Similarity with Lessons Learned from Word Embeddings”. Transactions of the Association for Computational Linguistics (Transactions of the Association for Computational Linguistics) 3: 211–225. doi:10.1162/tacl_a_00134.
Arora, S (Summer 2016). “A Latent Variable Model Approach to PMI-based Word Embeddings”. Transactions of Assoc. Of Comp. Linguistics 4: 385–399. doi:10.1162/tacl_a_00106. http://aclweb.org/anthology/Q16-1028.

arxiv.org

Mikolov, Tomas. "Efficient Estimation of Word Representations in Vector Space". arXiv:1301.3781 [cs.CL]。
Goldberg, Yoav; Levy, Omer. "word2vec Explained: Deriving Mikolov et al.'s Negative-Sampling Word-Embedding Method". arXiv:1402.3722 [cs.CL]。
Le, Quoc. "Distributed Representations of Sentences and Documents". arXiv:1405.4053 [cs.CL]。
Asgari, Ehsaneddin; Mofrad, Mohammad R.K. (2015). “Continuous Distributed Representation of Biological Sequences for Deep Proteomics and Genomics”. PLOS One 10 (11): e0141287. arXiv:1503.05140. Bibcode: 2015PLoSO..1041287A. doi:10.1371/journal.pone.0141287. PMC 4640716. PMID 26555596.
Ng, Patrick (2017). "dna2vec: Consistent vector representations of variable-length k-mers". arXiv:1701.06279 [q-bio.QM]。
Altszyler, E.; Ribeiro, S.; Sigman, M.; Fernández Slezak, D. (2017). “The interpretation of dream meaning: Resolving ambiguity using Latent Semantic Analysis in a small corpus of text”. Consciousness and Cognition 56: 178–187. arXiv:1610.01520. doi:10.1016/j.concog.2017.09.004. PMID 28943127.

code.google.com

“Google Code Archive - Long-term storage for Google Code Project Hosting.”. code.google.com. 2016年6月13日閲覧。

deeplearning4j.org

“Doc2Vec and Paragraph Vectors for Classification”. 2016年1月13日閲覧。

doi.org

Asgari, Ehsaneddin; Mofrad, Mohammad R.K. (2015). “Continuous Distributed Representation of Biological Sequences for Deep Proteomics and Genomics”. PLOS One 10 (11): e0141287. arXiv:1503.05140. Bibcode: 2015PLoSO..1041287A. doi:10.1371/journal.pone.0141287. PMC 4640716. PMID 26555596.
Banerjee, Imon; Chen, Matthew C.; Lungren, Matthew P.; Rubin, Daniel L. (2018). “Radiology report annotation using intelligent word embeddings: Applied to multi-institutional chest CT cohort”. Journal of Biomedical Informatics 77: 11–20. doi:10.1016/j.jbi.2017.11.012. PMC 5771955. PMID 29175548.
Levy, Omer; Goldberg, Yoav; Dagan, Ido (2015). “Improving Distributional Similarity with Lessons Learned from Word Embeddings”. Transactions of the Association for Computational Linguistics (Transactions of the Association for Computational Linguistics) 3: 211–225. doi:10.1162/tacl_a_00134.
Arora, S (Summer 2016). “A Latent Variable Model Approach to PMI-based Word Embeddings”. Transactions of Assoc. Of Comp. Linguistics 4: 385–399. doi:10.1162/tacl_a_00106. http://aclweb.org/anthology/Q16-1028.
Altszyler, E.; Ribeiro, S.; Sigman, M.; Fernández Slezak, D. (2017). “The interpretation of dream meaning: Resolving ambiguity using Latent Semantic Analysis in a small corpus of text”. Consciousness and Cognition 56: 178–187. arXiv:1610.01520. doi:10.1016/j.concog.2017.09.004. PMID 28943127.

github.com

“Doc2vec for IMDB sentiment analysis”. 2016年2月18日閲覧。

groups.google.com

“Parameter (hs & negative)”. Google Groups. 2016年6月13日閲覧。

harvard.edu

ui.adsabs.harvard.edu

Mikolov, Tomas; Sutskever, Ilya; Chen, Kai; Corrado, Greg S.; Dean, Jeff (2013). Distributed representations of words and phrases and their compositionality. Advances in Neural Information Processing Systems. Bibcode:2013arXiv1310.4546M。
Asgari, Ehsaneddin; Mofrad, Mohammad R.K. (2015). “Continuous Distributed Representation of Biological Sequences for Deep Proteomics and Genomics”. PLOS One 10 (11): e0141287. arXiv:1503.05140. Bibcode: 2015PLoSO..1041287A. doi:10.1371/journal.pone.0141287. PMC 4640716. PMID 26555596.

medium.com

“Doc2Vec tutorial using Gensim”. 2015年8月2日閲覧。

mit.edu

jmlr.csail.mit.edu

“Visualizing Data using t-SNE”. Journal of Machine Learning Research, 2008. Vol. 9, pg. 2595. 2017年3月18日閲覧。

nih.gov

pubmed.ncbi.nlm.nih.gov

Asgari, Ehsaneddin; Mofrad, Mohammad R.K. (2015). “Continuous Distributed Representation of Biological Sequences for Deep Proteomics and Genomics”. PLOS One 10 (11): e0141287. arXiv:1503.05140. Bibcode: 2015PLoSO..1041287A. doi:10.1371/journal.pone.0141287. PMC 4640716. PMID 26555596.
Banerjee, Imon; Chen, Matthew C.; Lungren, Matthew P.; Rubin, Daniel L. (2018). “Radiology report annotation using intelligent word embeddings: Applied to multi-institutional chest CT cohort”. Journal of Biomedical Informatics 77: 11–20. doi:10.1016/j.jbi.2017.11.012. PMC 5771955. PMID 29175548.
Altszyler, E.; Ribeiro, S.; Sigman, M.; Fernández Slezak, D. (2017). “The interpretation of dream meaning: Resolving ambiguity using Latent Semantic Analysis in a small corpus of text”. Consciousness and Cognition 56: 178–187. arXiv:1610.01520. doi:10.1016/j.concog.2017.09.004. PMID 28943127.

ncbi.nlm.nih.gov

Asgari, Ehsaneddin; Mofrad, Mohammad R.K. (2015). “Continuous Distributed Representation of Biological Sequences for Deep Proteomics and Genomics”. PLOS One 10 (11): e0141287. arXiv:1503.05140. Bibcode: 2015PLoSO..1041287A. doi:10.1371/journal.pone.0141287. PMC 4640716. PMID 26555596.
Banerjee, Imon; Chen, Matthew C.; Lungren, Matthew P.; Rubin, Daniel L. (2018). “Radiology report annotation using intelligent word embeddings: Applied to multi-institutional chest CT cohort”. Journal of Biomedical Informatics 77: 11–20. doi:10.1016/j.jbi.2017.11.012. PMC 5771955. PMID 29175548.

radimrehurek.com

“Gensim - Deep learning with word2vec”. 2016年6月10日閲覧。

youtube.com

Řehůřek, Radim. Word2vec and friends. 2015年8月14日閲覧。